Selection Bias and Covariate Imbalances (Statistics in Practice) - Tapa dura

Acerca del autor

Vance Berger is the author of Selection Bias and Covariate Imbalances in Randomized Clinical Trials, published by Wiley.

De la contraportada

Baseline data in clinical trials consists of information regarding patients that is measured at the outset, prior to randomization (or treatment with study medications). In studies where important baseline factors appear well balanced, it can be reasonably concluded that any differences in outcome between the intervention and control groups are a real effect of treatment. The common assumption that any baseline differences in a randomized study are necessarily random is, however, misplaced. Selection bias can, and does, occur – even in randomized clinical trials. Steps need to be taken in order to ensure that this does not compromise the integrity of clinical trials; hence Selection Bias and Covariate Imbalances in Randomized Clinical Trials offers the first comprehensive treatment of the subject and the methodology involved.

• Provides an overview of the hierarchy of study designs, and justifies the position of randomized trials at the top of this hierarchy.
• Discusses the strengths and defects of randomization, and provides real evidence to justify concern regarding its defects.
• Outlays the damaging consequences that selection bias causes when it does occur.
• Considers courses of action that can be taken to manage/contain the problem.
• Presents methods that can be used to detect selection bias in randomized trials, and methods to correct for selection bias.
• Concludes by providing a comprehensive plan for managing baseline imbalances and selection bias in randomized trials, and proposing open problems for future research.

Selection Bias and Covariate Imbalances in Randomized Clinical Trials provides an in-depth overview of a key aspect in the design and analysis of clinical trials, featuring modern and novel approaches to the methodology described. Illustrated with case studies, this book introduces groundbreaking ideas and research that will be invaluable to researchers and practitioners who design and analyse clinical trials. It will also be of interest to graduate students within the field of biostatistics.